The MindGarage originates in a movement of students, teachers, and friends who are interested in Deep Learning. It is closely connected to the development at the University of Kaiserslautern. The main milestones are the following:
Winter 2013: Marcus Liwicki becomes W3 substitute Professor (as Prof. Breuel left) at the University of Kaiserslautern and delivers lectures on Artificial Neural Networks and Data Mining
Summer 2015: The substitute Professorship ends as all PhD students finished their work - he concentrates on his position as “Maitre Assistant” at the University of Fribourg. As no lecturer offers a lecture on neural networks, Marcus guides the students through a self-study course on neural networks. However, Marcus continues supervising motivated Master students and mentors them for their future carreer.
Summer 2016: Highly motivated by students wish to have a subject on most recent Deep Learning technologies and strongly supported by Werner Weiss and his company Insiders Technologies GmbH, Marcus decided to establish a new lecture on Very Deep Learning. This lecture covers bleeding-edge technologies as well as deep investigation and analysis of Neural Networks and other Deep Learning strategies.
Autumn 2016: In order to let students do meaningful exercices, Insiders offers high-end GPU computers and the University of Kaiserslautern provides Marcus with three rooms which can be used for the exercises as well as for project an Master students supervised by Marcus. We call this independent “lab” the MindGarage
The Future: We (Team and Supporters) strongly believe that the MindGarage is just at it starting point and will become the perfect place for motivated students for discovering and exploring deep learning, evolving their ideas, investigating novel research ideas, and bringing newest technologies close to the industrial application!
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Seq2seq (2) Intro (2) Fun (3) Rnn (1) Event (9) Official (1) Lecture (1) Very deep learning (1) Footstep detection (1) Transfer learning (1) Publications (2) Ijcnn (1) Music information retrieval (1) Object recognition (1) Context representation (1) Arxiv (1) Image understanding (1) Image generation (1) Generative adversarial neural networks (1) Document classification (2) Deep learning architectures (2) Mindstorm (5) Segmentation (1) Documents (1) Deep learning (2) Gans (1) Adversarial (1) Teaching (1)